2020/08/21 by Raphael Tang, Tang, Raphael, Jaejun Lee +11 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Music and Audio Processing #Speech Recognition and Synthesis #Speech and Audio Processing #cs.CL #cs.LG
paper · pdf · doi:10.48550/arxiv.2008.09606
The first two authors contributed equally
arxiv created 2020/08/21 · openalex publication_date 2020/08/21 · arxiv updated 2020/08/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We describe Howl, an open-source wake word detection toolkit with native support for open speech datasets, like Mozilla Common Voice and Google Speech Commands. We report benchmark results on Speech Commands and our own freely available wake word detection dataset, built from MCV. We operationalize our system for Firefox Voice, a plugin enabling speech interactivity for the Firefox web browser. Howl represents, to the best of our knowledge, the first fully productionized yet open-source wake word detection toolkit with a web browser deployment target. Our codebase is at https://github.com/castorini/howl.